My research is focused on interactive machine learning. We see "big data" almost everywhere, but turning massive unlabeled text data into accurate models and reliable knowledge requires significant human effort. We can reduce the effort by enabling machine learning algorithms to interact with humans, and the classical "active learning" is a first step. Why sometimes uncertainty sampling learns even slower than random sampling? What if the data is only accessible via search (e.g. Google's Web index)? What if the interesting class is extremely rare (e.g. e-discovery)? What if the human has rich domain knowledge beyond class labels (e.g. medical domain)?